Exploration of the trait analysis for trait synchrony.

Parameters: environmental correction is TRUE.

Hypotheses

Check all hypotheses between traits and environmental drivers, and among traits

Big PCA

Trait_short Expected_direction Direct/indirect Disturbance ref_dist Resources ref_res Est CI Padj Fit_exp Mowing Grazing Fertil Est_nocorr CI_nocorr Fit_exp_nocorr
Arthropods (above, herbivores)
SLA ++ D
  • disturbance favours fast-growing species
NA
  • more nutrients allow for ‘cheap’ leaves
NA 0.44 0.29 - 0.58 0.0000000 0.47 0.27 0.07 0.48 0.34 - 0.62
Seed_mass D
  • disturbance selects for smaller seeds (= colonisation)
Diaz et al. 2016 NA NA -0.15 -0.31 - 0.01 0.1127329 Inconclusive -0.15 -0.10 -0.03 -0.07 -0.23 - 0.09 Inconclusive
LDMC D Tougher = slow NA NA NA -0.41 -0.56 - -0.26 0.0000000 -0.42 -0.44 -0.04 -0.40 -0.55 - -0.25
LeafN ++ D NA NA
  • more nutrients allow for ‘cheap’ leaves
Diaz et al. 2016 0.39 0.24 - 0.54 0.0000000 0.28 0.28 0.14 0.36 0.21 - 0.51
Arthropods (above, omnicarnivores)
LeafP ++ D NA NA
  • more nutrients allow for ‘cheap’ leaves
NA 0.51 0.37 - 0.65 0.0000000 0.37 0.40 0.20 0.47 0.33 - 0.61
Root_tissue_density D NA NA
  • conservative and/or ‘collaboration’ => if few nutrients, need for collaboration
Bergmann et al. 2020 -0.39 -0.54 - -0.24 0.0000000 -0.31 -0.29 -0.14 -0.30 -0.46 - -0.15
Arthropods (below, herbivores)
Aoc_BodySize D Smaller species evade disturbance more easily Birkhofer et al. 2015, 2017, see also Blake 1994, Neff et al. 2019, Simons et al. 2016 NA NA -0.06 -0.22 - 0.1 0.5717197 Inconclusive -0.01 -0.22 -0.04 -0.05 -0.22 - 0.11 Inconclusive
Aoc_Dispersal ++ D Disturbance selects for good dispersers to recolonize the plot after disturbance, Hanson et al. 2016 Birkhofer et al. 2013, 2015, 2017 , Simons et al. 2016 NA NA 0.33 0.18 - 0.49 0.0001175 0.51 0.17 -0.10 0.35 0.2 - 0.51
Ah_BodySize +/- D Smaller species evade disturbance more easily Birkhofer et al. 2015, 2017, see also Blake 1994, Neff et al. 2019, Simons et al. 2016 NA NA -0.09 -0.26 - 0.07 0.3571858 Inconclusive -0.19 -0.16 0.04 -0.17 -0.33 - -0.01 b
Arthropods (below, predators)
Ah_Dispersal ++ D Disturbance selects for good dispersers to recolonize the plot after disturbance, Hanson et al. 2016 Birkhofer et al. 2013, 2015, 2017 , Simons et al. 2016 NA NA 0.17 0.01 - 0.33 0.0763964 0.12 0.10 0.05 0.13 -0.03 - 0.29 Inconclusive
Ah_Generalism ++ NA NA NA NA NA 0.33 0.17 - 0.48 0.0001446 0.13 0.18 0.20 0.23 0.07 - 0.39
Bats
Ah_Generations ++ I NA NA NA NA 0.54 0.41 - 0.68 0.0000000 0.47 0.36 0.18 0.44 0.29 - 0.59
Aoc_b_BodySize D Smaller species evade disturbance more easily Birkhofer et al. 2015, 2017, see also Blake 1994, Neff et al. 2019, Simons et al. 2016 NA NA 0.07 -0.1 - 0.23 0.5136111 Inconclusive -0.06 0.02 0.13 0.07 -0.09 - 0.23 Inconclusive
Aoc_b_Dispersal ++ D Disturbance selects for good dispersers to recolonize the plot after disturbance, Hanson et al. 2016 Birkhofer et al. 2013, 2015, 2017 , Simons et al. 2016 NA NA 0.07 -0.09 - 0.23 0.5136111 Inconclusive 0.23 0.05 -0.10 0.08 -0.08 - 0.24 Inconclusive
Birds (insectivorous)
Ah_b_BodySize D Smaller species evade disturbance more easily Birkhofer et al. 2015, 2017, see also Blake 1994, Neff et al. 2019, Simons et al. 2016 NA NA -0.22 -0.41 - -0.04 0.0431460 -0.14 -0.27 -0.06 -0.21 -0.38 - -0.05
Ah_b_Dispersal ++ D Disturbance selects for good dispersers to recolonize the plot after disturbance, Hanson et al. 2016 Birkhofer et al. 2013, 2015, 2017 , Simons et al. 2016 NA NA 0.17 -0.02 - 0.35 0.1290393 Inconclusive -0.08 0.06 0.27 0.15 -0.02 - 0.32 Inconclusive
Ah_b_Generalism ++ NA NA NA NA NA -0.04 -0.23 - 0.15 0.7426961 Inconclusive 0.11 -0.01 -0.17 -0.11 -0.3 - 0.08 Inconclusive
Bi_Size ++ NA more = fast NA NA NA 0.21 0.05 - 0.37 0.0322472 0.37 0.20 -0.09 0.24 0.08 - 0.4
Bi_Incub ++ NA more = disturbance NA NA NA 0.09 -0.07 - 0.26 0.3642085 Inconclusive 0.33 0.10 -0.16 0.11 -0.05 - 0.28 Inconclusive
Butterflies
Bi_TOffsprings I Small = fast NA NA NA -0.07 -0.23 - 0.1 0.5136111 Inconclusive -0.35 -0.09 0.20 -0.07 -0.23 - 0.1 Inconclusive
Bi_GenLength NA NA NA NA NA 0.16 0 - 0.32 0.1004173 Inconclusive 0.36 0.18 -0.13 0.19 0.02 - 0.35 X
Bi_AgeMax I Small = fast NA NA NA 0.20 0.04 - 0.37 0.0330237 0.34 0.22 -0.09 0.24 0.08 - 0.4
but_flight ++ NA Early emergence favorable bc disturbance starts early Börschig et al. 2013 NA NA 0.36 0.21 - 0.51 0.0000427 0.40 0.26 0.09 0.21 0.05 - 0.37
but_GenYear ++ NA High reproduction can compensate mortality due to disturbance Börschig et al. 2013 NA NA 0.30 0.14 - 0.46 0.0006893 0.22 0.17 0.12 0.28 0.12 - 0.44
Collembola
but_hibernation ++ NA Later hibernation stage means butterflies ready before disturbance NA NA NA 0.35 0.2 - 0.51 0.0000427 0.33 0.27 0.12 0.26 0.1 - 0.42
but_Size ++ NA Larger wings = more dispersal Börschig et al. 2013 NA NA 0.21 0.05 - 0.37 0.0268176 0.12 0.06 0.17 0.07 -0.1 - 0.23 Inconclusive
but_Generalism ++ NA NA NA High nutrients = low plant diversity, hence more generalists NA 0.18 0.02 - 0.34 0.0665162 0.05 -0.03 0.19 0.13 -0.03 - 0.3 Inconclusive
col_Sex NA NA NA NA NA -0.02 -0.19 - 0.15 0.8354557 Inconclusive 0.04 0.02 -0.05 -0.03 -0.2 - 0.14 Inconclusive
Microbes
col_Gen_per_Year ++ NA Furca = escape disturbance NA NA NA -0.08 -0.25 - 0.09 0.5008186 Inconclusive 0.13 -0.11 -0.21 -0.07 -0.24 - 0.1 Inconclusive
col_Depth ++ NA NA NA NA NA -0.04 -0.21 - 0.13 0.7343040 Inconclusive -0.02 -0.13 -0.01 -0.02 -0.19 - 0.15 Inconclusive
col_Size NA a/ more resources or b/ selected NA NA NA 0.00 -0.16 - 0.17 0.9549500 Inconclusive -0.14 -0.01 0.14 0.00 -0.17 - 0.17 Inconclusive
mites_DaysAdult NA longer lifespan = slow NA NA NA -0.12 -0.29 - 0.04 0.2116668 Inconclusive -0.16 -0.15 0.01 -0.10 -0.27 - 0.07 Inconclusive
mites_Mass NA Mass = size = slow NA NA NA -0.14 -0.3 - 0.03 0.1564787 Inconclusive -0.07 -0.19 -0.07 -0.13 -0.29 - 0.04 Inconclusive
Mites
mites_Sex I Habitat openness = sexual repro, more LUI = more growth NA NA NA -0.04 -0.21 - 0.12 0.6884583 Inconclusive 0.09 -0.01 -0.13 -0.03 -0.19 - 0.14 Inconclusive
mites_Hab_spec ++ NA more disturbance = more in the soil NA NA NA -0.02 -0.19 - 0.15 0.8354557 Inconclusive -0.13 -0.05 0.10 -0.02 -0.19 - 0.14 Inconclusive
mites_Feed_spec ++ NA NA NA NA NA 0.16 -0.01 - 0.32 0.1078041 Inconclusive 0.19 0.11 0.01 0.18 0.01 - 0.34
P_patho ++ NA More bacteria = more bacterivores NA NA NA -0.06 -0.22 - 0.1 0.5717197 Inconclusive -0.08 -0.14 0.05 -0.06 -0.22 - 0.1 Inconclusive
Pb_Size NA a/ More nutrients = more resources to grow. b/ Disturbance selects smaller size NA NA NA -0.16 -0.32 - 0 0.1004173 Inconclusive -0.15 -0.07 -0.04 -0.12 -0.29 - 0.04 Inconclusive
Plants (AG)
Ps_Size NA a/ More nutrients = more resources to grow. b/ Disturbance selects smaller size NA NA NA -0.17 -0.33 - -0.01 0.0814530 0.04 -0.03 -0.24 -0.13 -0.29 - 0.03 Inconclusive
mic_FB D and I Fungi slower than bacteria, linked to slow plant traits NA Fungi dominate in low-nutrient soils; associated with slow plants de Vries et al. 2006, de Vries et al. 2012, Boeddinghaus et al. 2019 -0.37 -0.52 - -0.22 0.0000000 -0.22 -0.37 -0.18 -0.24 -0.4 - -0.08
mic_Fpathotroph ++ NA Fast= more parasites check https://www.nature.com/articles/s41467-021-23605-y Fast plant invest less in defenses, so more pathogens NA 0.42 0.27 - 0.56 0.0000000 0.19 0.47 0.22 0.31 0.15 - 0.46
mic_O.C.ratio NA NA NA
  • more oligo (Acido) than copio (Actibo, alphapto…) in slow
Check Neff 2015, Ramirez 2010, Fierer 2012 -0.29 -0.45 - -0.14 0.0007344 -0.03 -0.18 -0.24 -0.14 -0.3 - 0.02 Inconclusive
mic_Bvolume +/- D a/ small cells more efficient for diffusive uptake (-) OR b/ for a given substrate demand, large radius compensates low substrate concentrations Westoby et al. 2021 NA NA -0.35 -0.5 - -0.19 0.0000427 B -0.20 -0.32 -0.16 -0.36 -0.52 - -0.21 B
Plants (BG)
mic_Bgenome_size D NA NA
  • Larger genomes should be more successful in resource-poor environments v. S strategies have smaller genomes (Westoby et al.)
Leff et al. 2015; Konstantinidis (2004) -0.30 -0.45 - -0.14 0.0006893 -0.28 -0.28 -0.08 -0.09 -0.25 - 0.07 Inconclusive
Protists
bat_mass NA Large more sensitive to disturbance BUT large less sensitive to urbanisation?? Farneda et al. 2015, Moir et al. 2021 , Jung et al 2018 NA NA -0.16 -0.32 - 0 0.0928054 -0.13 -0.19 -0.06 -0.22 -0.38 - -0.06
Protists bacterivores
bat_lifespan NA NA NA NA NA NA 0.04 -0.13 - 0.2 0.7343040 Inconclusive -0.01 -0.03 0.05 0.06 -0.1 - 0.23 Inconclusive
Protists predators
bat_offspring ++ NA opposite to size NA NA NA -0.11 -0.27 - 0.05 0.2718950 Inconclusive 0.01 0.02 -0.15 -0.16 -0.32 - 0 X

Identification of strategy axes for each group

Plants, above- and below-ground

Trait_short Expected_direction Direct/indirect Disturbance ref_dist Resources ref_res Est CI Padj Fit_exp Mowing Grazing Fertil Est_nocorr CI_nocorr Fit_exp_nocorr
Plants (AG)
SLA ++ D
  • disturbance favours fast-growing species
NA
  • more nutrients allow for ‘cheap’ leaves
NA 0.44 0.29 - 0.58 0.0000000 0.47 0.27 0.07 0.48 0.34 - 0.62
Seed_mass D
  • disturbance selects for smaller seeds (= colonisation)
Diaz et al. 2016 NA NA -0.15 -0.31 - 0.01 0.1127329 Inconclusive -0.15 -0.10 -0.03 -0.07 -0.23 - 0.09 Inconclusive
LDMC D Tougher = slow NA NA NA -0.41 -0.56 - -0.26 0.0000000 -0.42 -0.44 -0.04 -0.40 -0.55 - -0.25
LeafN ++ D NA NA
  • more nutrients allow for ‘cheap’ leaves
Diaz et al. 2016 0.39 0.24 - 0.54 0.0000000 0.28 0.28 0.14 0.36 0.21 - 0.51
LeafP ++ D NA NA
  • more nutrients allow for ‘cheap’ leaves
NA 0.51 0.37 - 0.65 0.0000000 0.37 0.40 0.20 0.47 0.33 - 0.61
Plants (BG)
Root_tissue_density D NA NA
  • conservative and/or ‘collaboration’ => if few nutrients, need for collaboration
Bergmann et al. 2020 -0.39 -0.54 - -0.24 0.0000000 -0.31 -0.29 -0.14 -0.30 -0.46 - -0.15
## [1] "Plants, All"
## Registered S3 methods overwritten by 'car':
##   method                          from
##   influence.merMod                lme4
##   cooks.distance.influence.merMod lme4
##   dfbeta.influence.merMod         lme4
##   dfbetas.influence.merMod        lme4

Bacteria & fungi

Trait_short Expected_direction Direct/indirect Disturbance ref_dist Resources ref_res Est CI Padj Fit_exp Mowing Grazing Fertil Est_nocorr CI_nocorr Fit_exp_nocorr
Microbes
mic_FB D and I Fungi slower than bacteria, linked to slow plant traits NA Fungi dominate in low-nutrient soils; associated with slow plants de Vries et al. 2006, de Vries et al. 2012, Boeddinghaus et al. 2019 -0.37 -0.52 - -0.22 0.0000000 -0.22 -0.37 -0.18 -0.24 -0.4 - -0.08
mic_Fpathotroph ++ NA Fast= more parasites check https://www.nature.com/articles/s41467-021-23605-y Fast plant invest less in defenses, so more pathogens NA 0.42 0.27 - 0.56 0.0000000 0.19 0.47 0.22 0.31 0.15 - 0.46
mic_O.C.ratio NA NA NA
  • more oligo (Acido) than copio (Actibo, alphapto…) in slow
Check Neff 2015, Ramirez 2010, Fierer 2012 -0.29 -0.45 - -0.14 0.0007344 -0.03 -0.18 -0.24 -0.14 -0.3 - 0.02 Inconclusive
mic_Bvolume +/- D a/ small cells more efficient for diffusive uptake (-) OR b/ for a given substrate demand, large radius compensates low substrate concentrations Westoby et al. 2021 NA NA -0.35 -0.5 - -0.19 0.0000427 B -0.20 -0.32 -0.16 -0.36 -0.52 - -0.21 B
mic_Bgenome_size D NA NA
  • Larger genomes should be more successful in resource-poor environments v. S strategies have smaller genomes (Westoby et al.)
Leff et al. 2015; Konstantinidis (2004) -0.30 -0.45 - -0.14 0.0006893 -0.28 -0.28 -0.08 -0.09 -0.25 - 0.07 Inconclusive

Arthropods, above-ground

Herbivores

Trait_short Expected_direction Direct/indirect Disturbance ref_dist Resources ref_res Est CI Padj Fit_exp Mowing Grazing Fertil Est_nocorr CI_nocorr Fit_exp_nocorr
Arthropods (above, herbivores)
Aoc_BodySize D Smaller species evade disturbance more easily Birkhofer et al. 2015, 2017, see also Blake 1994, Neff et al. 2019, Simons et al. 2016 NA NA -0.06 -0.22 - 0.1 0.5717197 Inconclusive -0.01 -0.22 -0.04 -0.05 -0.22 - 0.11 Inconclusive
Aoc_Dispersal ++ D Disturbance selects for good dispersers to recolonize the plot after disturbance, Hanson et al. 2016 Birkhofer et al. 2013, 2015, 2017 , Simons et al. 2016 NA NA 0.33 0.18 - 0.49 0.0001175 0.51 0.17 -0.10 0.35 0.2 - 0.51
Ah_BodySize +/- D Smaller species evade disturbance more easily Birkhofer et al. 2015, 2017, see also Blake 1994, Neff et al. 2019, Simons et al. 2016 NA NA -0.09 -0.26 - 0.07 0.3571858 Inconclusive -0.19 -0.16 0.04 -0.17 -0.33 - -0.01 b
Ah_Dispersal ++ D Disturbance selects for good dispersers to recolonize the plot after disturbance, Hanson et al. 2016 Birkhofer et al. 2013, 2015, 2017 , Simons et al. 2016 NA NA 0.17 0.01 - 0.33 0.0763964 0.12 0.10 0.05 0.13 -0.03 - 0.29 Inconclusive
Arthropods (above, omnicarnivores)
Ah_Generalism ++ NA NA NA NA NA 0.33 0.17 - 0.48 0.0001446 0.13 0.18 0.20 0.23 0.07 - 0.39
Ah_Generations ++ I NA NA NA NA 0.54 0.41 - 0.68 0.0000000 0.47 0.36 0.18 0.44 0.29 - 0.59
Arthropods (below, herbivores)
Aoc_b_BodySize D Smaller species evade disturbance more easily Birkhofer et al. 2015, 2017, see also Blake 1994, Neff et al. 2019, Simons et al. 2016 NA NA 0.07 -0.1 - 0.23 0.5136111 Inconclusive -0.06 0.02 0.13 0.07 -0.09 - 0.23 Inconclusive
Aoc_b_Dispersal ++ D Disturbance selects for good dispersers to recolonize the plot after disturbance, Hanson et al. 2016 Birkhofer et al. 2013, 2015, 2017 , Simons et al. 2016 NA NA 0.07 -0.09 - 0.23 0.5136111 Inconclusive 0.23 0.05 -0.10 0.08 -0.08 - 0.24 Inconclusive
Ah_b_BodySize D Smaller species evade disturbance more easily Birkhofer et al. 2015, 2017, see also Blake 1994, Neff et al. 2019, Simons et al. 2016 NA NA -0.22 -0.41 - -0.04 0.0431460 -0.14 -0.27 -0.06 -0.21 -0.38 - -0.05
Arthropods (below, predators)
Ah_b_Dispersal ++ D Disturbance selects for good dispersers to recolonize the plot after disturbance, Hanson et al. 2016 Birkhofer et al. 2013, 2015, 2017 , Simons et al. 2016 NA NA 0.17 -0.02 - 0.35 0.1290393 Inconclusive -0.08 0.06 0.27 0.15 -0.02 - 0.32 Inconclusive
Ah_b_Generalism ++ NA NA NA NA NA -0.04 -0.23 - 0.15 0.7426961 Inconclusive 0.11 -0.01 -0.17 -0.11 -0.3 - 0.08 Inconclusive
Trait_short Expected_direction Direct/indirect Disturbance ref_dist Resources ref_res Est CI Padj Fit_exp Mowing Grazing Fertil Est_nocorr CI_nocorr Fit_exp_nocorr
Butterflies
but_flight ++ NA Early emergence favorable bc disturbance starts early Börschig et al. 2013 NA NA 0.36 0.21 - 0.51 0.0000427 0.40 0.26 0.09 0.21 0.05 - 0.37
but_GenYear ++ NA High reproduction can compensate mortality due to disturbance Börschig et al. 2013 NA NA 0.30 0.14 - 0.46 0.0006893 0.22 0.17 0.12 0.28 0.12 - 0.44
but_hibernation ++ NA Later hibernation stage means butterflies ready before disturbance NA NA NA 0.35 0.2 - 0.51 0.0000427 0.33 0.27 0.12 0.26 0.1 - 0.42
but_Size ++ NA Larger wings = more dispersal Börschig et al. 2013 NA NA 0.21 0.05 - 0.37 0.0268176 0.12 0.06 0.17 0.07 -0.1 - 0.23 Inconclusive
but_Generalism ++ NA NA NA High nutrients = low plant diversity, hence more generalists NA 0.18 0.02 - 0.34 0.0665162 0.05 -0.03 0.19 0.13 -0.03 - 0.3 Inconclusive

Predators

Trait_short Expected_direction Direct/indirect Disturbance ref_dist Resources ref_res Est CI Padj Fit_exp Mowing Grazing Fertil Est_nocorr CI_nocorr Fit_exp_nocorr
Arthropods (above, omnicarnivores)
Aoc_BodySize D Smaller species evade disturbance more easily Birkhofer et al. 2015, 2017, see also Blake 1994, Neff et al. 2019, Simons et al. 2016 NA NA -0.06 -0.22 - 0.1 0.5717197 Inconclusive -0.01 -0.22 -0.04 -0.05 -0.22 - 0.11 Inconclusive
Aoc_Dispersal ++ D Disturbance selects for good dispersers to recolonize the plot after disturbance, Hanson et al. 2016 Birkhofer et al. 2013, 2015, 2017 , Simons et al. 2016 NA NA 0.33 0.18 - 0.49 0.0001175 0.51 0.17 -0.10 0.35 0.2 - 0.51
Arthropods (below, predators)
Aoc_b_BodySize D Smaller species evade disturbance more easily Birkhofer et al. 2015, 2017, see also Blake 1994, Neff et al. 2019, Simons et al. 2016 NA NA 0.07 -0.1 - 0.23 0.5136111 Inconclusive -0.06 0.02 0.13 0.07 -0.09 - 0.23 Inconclusive
Aoc_b_Dispersal ++ D Disturbance selects for good dispersers to recolonize the plot after disturbance, Hanson et al. 2016 Birkhofer et al. 2013, 2015, 2017 , Simons et al. 2016 NA NA 0.07 -0.09 - 0.23 0.5136111 Inconclusive 0.23 0.05 -0.10 0.08 -0.08 - 0.24 Inconclusive

Protists

Trait_short Expected_direction Direct/indirect Disturbance ref_dist Resources ref_res Est CI Padj Fit_exp Mowing Grazing Fertil Est_nocorr CI_nocorr Fit_exp_nocorr
Protists
P_patho ++ NA More bacteria = more bacterivores NA NA NA -0.06 -0.22 - 0.1 0.5717197 Inconclusive -0.08 -0.14 0.05 -0.06 -0.22 - 0.1 Inconclusive
Protists bacterivores
Pb_Size NA a/ More nutrients = more resources to grow. b/ Disturbance selects smaller size NA NA NA -0.16 -0.32 - 0 0.1004173 Inconclusive -0.15 -0.07 -0.04 -0.12 -0.29 - 0.04 Inconclusive
Protists predators
Ps_Size NA a/ More nutrients = more resources to grow. b/ Disturbance selects smaller size NA NA NA -0.17 -0.33 - -0.01 0.0814530 0.04 -0.03 -0.24 -0.13 -0.29 - 0.03 Inconclusive

Birds

Trait_short Expected_direction Direct/indirect Disturbance ref_dist Resources ref_res Est CI Padj Fit_exp Mowing Grazing Fertil Est_nocorr CI_nocorr Fit_exp_nocorr
Birds (insectivorous)
Bi_Size ++ NA more = fast NA NA NA 0.21 0.05 - 0.37 0.0322472 0.37 0.20 -0.09 0.24 0.08 - 0.4
Bi_Incub ++ NA more = disturbance NA NA NA 0.09 -0.07 - 0.26 0.3642085 Inconclusive 0.33 0.10 -0.16 0.11 -0.05 - 0.28 Inconclusive
Bi_TOffsprings I Small = fast NA NA NA -0.07 -0.23 - 0.1 0.5136111 Inconclusive -0.35 -0.09 0.20 -0.07 -0.23 - 0.1 Inconclusive
Bi_GenLength NA NA NA NA NA 0.16 0 - 0.32 0.1004173 Inconclusive 0.36 0.18 -0.13 0.19 0.02 - 0.35 X
Bi_AgeMax I Small = fast NA NA NA 0.20 0.04 - 0.37 0.0330237 0.34 0.22 -0.09 0.24 0.08 - 0.4

Mites & collembola

Trait_short Expected_direction Direct/indirect Disturbance ref_dist Resources ref_res Est CI Padj Fit_exp Mowing Grazing Fertil Est_nocorr CI_nocorr Fit_exp_nocorr
Mites
mites_DaysAdult NA longer lifespan = slow NA NA NA -0.12 -0.29 - 0.04 0.2116668 Inconclusive -0.16 -0.15 0.01 -0.10 -0.27 - 0.07 Inconclusive
mites_Mass NA Mass = size = slow NA NA NA -0.14 -0.3 - 0.03 0.1564787 Inconclusive -0.07 -0.19 -0.07 -0.13 -0.29 - 0.04 Inconclusive
mites_Sex I Habitat openness = sexual repro, more LUI = more growth NA NA NA -0.04 -0.21 - 0.12 0.6884583 Inconclusive 0.09 -0.01 -0.13 -0.03 -0.19 - 0.14 Inconclusive
mites_Hab_spec ++ NA more disturbance = more in the soil NA NA NA -0.02 -0.19 - 0.15 0.8354557 Inconclusive -0.13 -0.05 0.10 -0.02 -0.19 - 0.14 Inconclusive
mites_Feed_spec ++ NA NA NA NA NA 0.16 -0.01 - 0.32 0.1078041 Inconclusive 0.19 0.11 0.01 0.18 0.01 - 0.34
## NULL

Trait_short Expected_direction Direct/indirect Disturbance ref_dist Resources ref_res Est CI Padj Fit_exp Mowing Grazing Fertil Est_nocorr CI_nocorr Fit_exp_nocorr
Collembola
col_Sex NA NA NA NA NA -0.02 -0.19 - 0.15 0.8354557 Inconclusive 0.04 0.02 -0.05 -0.03 -0.2 - 0.14 Inconclusive
col_Gen_per_Year ++ NA Furca = escape disturbance NA NA NA -0.08 -0.25 - 0.09 0.5008186 Inconclusive 0.13 -0.11 -0.21 -0.07 -0.24 - 0.1 Inconclusive
col_Depth ++ NA NA NA NA NA -0.04 -0.21 - 0.13 0.7343040 Inconclusive -0.02 -0.13 -0.01 -0.02 -0.19 - 0.15 Inconclusive
col_Size NA a/ more resources or b/ selected NA NA NA 0.00 -0.16 - 0.17 0.9549500 Inconclusive -0.14 -0.01 0.14 0.00 -0.17 - 0.17 Inconclusive
## NULL

Bats

Trait_short Expected_direction Direct/indirect Disturbance ref_dist Resources ref_res Est CI Padj Fit_exp Mowing Grazing Fertil Est_nocorr CI_nocorr Fit_exp_nocorr
Bats
bat_mass NA Large more sensitive to disturbance BUT large less sensitive to urbanisation?? Farneda et al. 2015, Moir et al. 2021 , Jung et al 2018 NA NA -0.16 -0.32 - 0 0.0928054 -0.13 -0.19 -0.06 -0.22 -0.38 - -0.06
bat_lifespan NA NA NA NA NA NA 0.04 -0.13 - 0.2 0.7343040 Inconclusive -0.01 -0.03 0.05 0.06 -0.1 - 0.23 Inconclusive
bat_offspring ++ NA opposite to size NA NA NA -0.11 -0.27 - 0.05 0.2718950 Inconclusive 0.01 0.02 -0.15 -0.16 -0.32 - 0 X
## NULL

Try to do a SEM

## 
##  Pearson's product-moment correlation
## 
## data:  PCA_pca$ind$coord[, 1] and env_data_lui[Plot %in% dd$Plot, ]$LUI
## t = 9.7547, df = 148, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  0.5171512 0.7142237
## sample estimates:
##       cor 
## 0.6255661

Run above-ground model, simple

## [1] "Direct"
## [1] "Indirect"
## [1] "Total"
## [1] "Direct"
## [1] "Indirect"
## [1] "Total"
## [1] "Direct"
## [1] "Indirect"
## [1] "Total"
## [1] "Direct"
## [1] "Indirect"
## [1] "Total"
##            cfi          rmsea rmsea.ci.upper            bic 
##          0.993          0.070          0.242       2520.742
## quartz_off_screen 
##                 2

Run below-ground model, simple

## lavaan 0.6-9 ended normally after 21 iterations
## 
##   Estimator                                         ML
##   Optimization method                           NLMINB
##   Number of model parameters                        40
##                                                       
##                                                   Used       Total
##   Number of observations                           130         150
##                                                                   
## Model Test User Model:
##                                                       
##   Test statistic                                 3.547
##   Degrees of freedom                                 4
##   P-value (Chi-square)                           0.471
## 
## Parameter Estimates:
## 
##   Standard errors                             Standard
##   Information                                 Expected
##   Information saturated (h1) model          Structured
## 
## Regressions:
##                          Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##   plant ~                                                                     
##     LUI                     0.539    0.077    7.036    0.000    0.539    0.525
##   Protists_patho ~                                                            
##     LUI                     0.077    0.102    0.751    0.453    0.077    0.077
##     plant                  -0.142    0.100   -1.423    0.155   -0.142   -0.146
##   Microbes ~                                                                  
##     LUI                     0.163    0.072    2.259    0.024    0.163    0.159
##     plant                   0.632    0.070    8.982    0.000    0.632    0.633
##   Protists_bact ~                                                             
##     LUI                     0.161    0.100    1.607    0.108    0.161    0.161
##     plant                   0.124    0.122    1.021    0.307    0.124    0.128
##     Microbes                0.012    0.119    0.103    0.918    0.012    0.013
##     Protists_patho          0.159    0.084    1.904    0.057    0.159    0.161
##   Protists_sec ~                                                              
##     LUI                     0.182    0.106    1.720    0.085    0.182    0.177
##     Protists_bact          -0.070    0.092   -0.765    0.444   -0.070   -0.068
##     plant                   0.203    0.128    1.583    0.113    0.203    0.203
##     Microbes               -0.216    0.125   -1.737    0.082   -0.216   -0.216
##     Protists_patho         -0.043    0.089   -0.489    0.625   -0.043   -0.043
##   Mites ~                                                                     
##     LUI                     0.171    0.098    1.733    0.083    0.171    0.176
##     plant                   0.147    0.119    1.236    0.217    0.147    0.156
##     Microbes               -0.289    0.116   -2.492    0.013   -0.289   -0.306
##     Protists_sec           -0.036    0.081   -0.445    0.656   -0.036   -0.038
##     Protists_bact           0.016    0.085    0.193    0.847    0.016    0.017
##     Protists_patho         -0.219    0.082   -2.675    0.007   -0.219   -0.227
##   Coll ~                                                                      
##     LUI                    -0.045    0.104   -0.431    0.667   -0.045   -0.045
##     Microbes                0.119    0.122    0.969    0.332    0.119    0.123
##     plant                  -0.073    0.126   -0.584    0.559   -0.073   -0.077
##     Protists_sec           -0.024    0.085   -0.282    0.778   -0.024   -0.025
##     Protists_bact           0.080    0.090    0.891    0.373    0.080    0.081
##     Protists_patho         -0.162    0.086   -1.879    0.060   -0.162   -0.165
##   Arth_omnicarni_below ~                                                      
##     LUI                     0.038    0.099    0.384    0.701    0.038    0.039
##     Mites                   0.177    0.089    1.993    0.046    0.177    0.174
##     Coll                   -0.123    0.086   -1.443    0.149   -0.123   -0.124
##     Protists_sec           -0.148    0.083   -1.794    0.073   -0.148   -0.154
##     plant                  -0.063    0.096   -0.654    0.513   -0.063   -0.066
##     Protists_patho          0.003    0.087    0.031    0.975    0.003    0.003
## 
## Variances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##    .plant             0.773    0.096    8.062    0.000    0.773    0.724
##    .Protists_patho    1.002    0.124    8.062    0.000    1.002    0.985
##    .Microbes          0.497    0.062    8.062    0.000    0.497    0.468
##    .Protists_bact     0.912    0.113    8.062    0.000    0.912    0.910
##    .Protists_sec      1.002    0.124    8.062    0.000    1.002    0.942
##    .Mites             0.849    0.105    8.062    0.000    0.849    0.897
##    .Coll              0.946    0.117    8.062    0.000    0.946    0.962
##    .Arth_mncrn_blw    0.911    0.113    8.062    0.000    0.911    0.929
## lavaan 0.6-9 ended normally after 19 iterations
## 
##   Estimator                                         ML
##   Optimization method                           NLMINB
##   Number of model parameters                        36
##                                                       
##                                                   Used       Total
##   Number of observations                           130         150
##                                                                   
## Model Test User Model:
##                                                       
##   Test statistic                                18.086
##   Degrees of freedom                                 8
##   P-value (Chi-square)                           0.021
## 
## Parameter Estimates:
## 
##   Standard errors                             Standard
##   Information                                 Expected
##   Information saturated (h1) model          Structured
## 
## Regressions:
##                          Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##   plant ~                                                                     
##     LUI                     0.539    0.077    7.036    0.000    0.539    0.525
##   Protists_patho ~                                                            
##     LUI                     0.077    0.102    0.752    0.452    0.077    0.077
##     plant                  -0.142    0.100   -1.425    0.154   -0.142   -0.146
##   Microbes ~                                                                  
##     LUI                     0.163    0.072    2.259    0.024    0.163    0.159
##     plant                   0.632    0.070    8.982    0.000    0.632    0.633
##   Protists_bact ~                                                             
##     LUI                     0.174    0.101    1.720    0.085    0.174    0.175
##     plant                   0.106    0.123    0.860    0.390    0.106    0.109
##     Microbes                0.006    0.120    0.049    0.961    0.006    0.006
##   Protists_sec ~                                                              
##     LUI                     0.180    0.106    1.697    0.090    0.180    0.175
##     plant                   0.209    0.128    1.637    0.102    0.209    0.209
##     Microbes               -0.215    0.125   -1.722    0.085   -0.215   -0.214
##     Protists_bact          -0.078    0.091   -0.857    0.392   -0.078   -0.075
##   Mites ~                                                                     
##     LUI                     0.157    0.101    1.556    0.120    0.157    0.163
##     plant                   0.175    0.122    1.437    0.151    0.175    0.186
##     Microbes               -0.278    0.119   -2.336    0.020   -0.278   -0.295
##     Protists_sec           -0.027    0.083   -0.322    0.748   -0.027   -0.028
##     Protists_bact          -0.020    0.086   -0.234    0.815   -0.020   -0.021
##   Coll ~                                                                      
##     LUI                    -0.055    0.105   -0.520    0.603   -0.055   -0.056
##     plant                  -0.053    0.127   -0.417    0.676   -0.053   -0.055
##     Microbes                0.127    0.124    1.022    0.307    0.127    0.132
##     Protists_bact           0.053    0.090    0.588    0.557    0.053    0.053
##     Protists_sec           -0.017    0.086   -0.199    0.842   -0.017   -0.018
##   Arth_omnicarni_below ~                                                      
##     LUI                    -0.004    0.087   -0.040    0.968   -0.004   -0.004
##     Mites                   0.177    0.087    2.035    0.042    0.177    0.173
##     Coll                   -0.128    0.085   -1.510    0.131   -0.128   -0.128
##     Protists_sec           -0.149    0.083   -1.809    0.070   -0.149   -0.156
##     Protists_bact           0.034    0.086    0.392    0.695    0.034    0.034
## 
## Covariances:
##                     Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##  .Protists_patho ~~                                                      
##    .Arth_mncrn_blw    -0.003    0.084   -0.042    0.967   -0.003   -0.004
## 
## Variances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##    .plant             0.773    0.096    8.062    0.000    0.773    0.724
##    .Protists_patho    1.002    0.124    8.062    0.000    1.002    0.985
##    .Microbes          0.497    0.062    8.062    0.000    0.497    0.468
##    .Protists_bact     0.937    0.116    8.062    0.000    0.937    0.935
##    .Protists_sec      1.004    0.125    8.062    0.000    1.004    0.944
##    .Mites             0.895    0.111    8.062    0.000    0.895    0.949
##    .Coll              0.972    0.121    8.062    0.000    0.972    0.987
##    .Arth_mncrn_blw    0.913    0.113    8.062    0.000    0.913    0.930
##            cfi          rmsea rmsea.ci.upper            bic 
##          0.936          0.098          0.160       2964.807
## [1] "Direct"
## [1] "Indirect"
## [1] "Total"
## [1] "Direct"
## [1] "Indirect"
## [1] "Total"
## [1] "Direct"
## [1] "Indirect"
## [1] "Total"
## [1] "Direct"
## [1] "Indirect"
## [1] "Total"
##            cfi          rmsea rmsea.ci.upper            bic 
##          0.936          0.095          0.152       3369.102
## quartz_off_screen 
##                 2

Use the parameters defined in the simple SEM

## 
## Attaching package: 'scales'
## The following object is masked from 'package:purrr':
## 
##     discard
## The following object is masked from 'package:readr':
## 
##     col_factor
## The following object is masked from 'package:viridis':
## 
##     viridis_pal
## Scale for 'size' is already present. Adding another scale for 'size', which
## will replace the existing scale.

## Run above-ground model, full model

Run below-ground model, full lui components

Use the parameters defined in the complex SEMs

get multidiv

## `set.seed(1)` was used to initialize repeatable random subsampling.
## Please record this for your records so others can reproduce.
## Try `set.seed(1); .Random.seed` for the full vector
## ...
## 50OTUs were removed because they are no longer 
## present in any sample after random subsampling
## ...
## `set.seed(1)` was used to initialize repeatable random subsampling.
## Please record this for your records so others can reproduce.
## Try `set.seed(1); .Random.seed` for the full vector
## ...
## 11288OTUs were removed because they are no longer 
## present in any sample after random subsampling
## ...

Check effect on EF MF

## [1] 496
## [1] 496
## quartz_off_screen 
##                 2
## quartz_off_screen 
##                 2
## 
##  Pearson's product-moment correlation
## 
## data:  Dim.1_all and Dim.1_fun
## t = 11.857, df = 148, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  0.6054364 0.7718934
## sample estimates:
##       cor 
## 0.6979747
## Start:  AIC=-44.48
## Dim.1_fun ~ Dim.1_all
## 
##             Df Sum of Sq    RSS     AIC
## <none>                   108.58 -44.475
## - Dim.1_all  1    103.14 211.72  53.696
## Start:  AIC=-31.44
## Dim.1_fun ~ Dim.1_mic
## 
##             Df Sum of Sq    RSS     AIC
## <none>                   118.44 -31.438
## - Dim.1_mic  1    93.286 211.72  53.696
## Start:  AIC=-19.43
## Dim.1_fun ~ Dim.1_plants
## 
##                Df Sum of Sq    RSS     AIC
## <none>                      128.31 -19.434
## - Dim.1_plants  1    83.418 211.72  53.696
## Start:  AIC=34.29
## Dim.1_fun ~ multidiv
## 
##            Df Sum of Sq    RSS    AIC
## <none>                  183.57 34.291
## - multidiv  1    28.156 211.72 53.696
## Start:  AIC=-4.18
## Dim.1_fun ~ LUI
## 
##        Df Sum of Sq    RSS    AIC
## <none>              142.04 -4.177
## - LUI   1    69.681 211.72 53.696
##                                                Model Estimate (sd)
## 1   Functions slow-fast ~ entire community slow-fast   0.56 (0.05)
## 2             Functions slow-fast ~ plants slow-fast   0.38 (0.04)
## 3 Functions slow-fast ~ bacteria and fungi slow-fast  -0.52 (0.05)
## 4                          Functions slow-fast ~ LUI   0.68 (0.08)
## 5     Functions slow-fast ~ taxonomic multidiversity  -0.43 (0.09)
##                   Pval   R2        adj.P
## 1 3.21625727911058e-23 0.48 1.608129e-22
## 2 8.26295515599654e-18 0.39 1.377159e-17
## 3 2.09759862872059e-20 0.44 5.243997e-20
## 4 1.67387903688761e-14 0.32 2.092349e-14
## 5  4.4768570590818e-06 0.13 4.476857e-06
## lavaan 0.6-9 ended normally after 14 iterations
## 
##   Estimator                                         ML
##   Optimization method                           NLMINB
##   Number of model parameters                         5
##                                                       
##   Number of observations                           150
##                                                       
## Model Test User Model:
##                                                       
##   Test statistic                                 0.000
##   Degrees of freedom                                 0
## 
## Parameter Estimates:
## 
##   Standard errors                            Bootstrap
##   Number of requested bootstrap draws             1000
##   Number of successful bootstrap draws            1000
## 
## Regressions:
##                    Estimate  Std.Err  z-value  P(>|z|)
##   Dim.1_fun ~                                         
##     LUI        (d)    0.268    0.087    3.077    0.002
##     Dim.1_all  (a)    0.444    0.049    8.979    0.000
##   Dim.1_all ~                                         
##     LUI        (b)    0.935    0.102    9.210    0.000
## 
## Variances:
##                    Estimate  Std.Err  z-value  P(>|z|)
##    .Dim.1_fun         0.680    0.090    7.519    0.000
##    .Dim.1_all         1.351    0.165    8.174    0.000
## 
## Defined Parameters:
##                    Estimate  Std.Err  z-value  P(>|z|)
##     indirect          0.415    0.071    5.853    0.000
##     total             0.684    0.064   10.741    0.000
##     diff              0.147    0.146    1.008    0.313
## quartz_off_screen 
##                 2